Symptoms occurring immediately before and during menstruation are estimated to affect 30-50% of women, prompt 1.5 million physician visits annually, and interfere with labor force productivity. However, prevalence estimates of perimenstrual symptoms (PS) among adult US women are based on studies of highly selected populations. The multidimensional nature of PS is poorly specified, and a typology of PS is needed for future case-control studies of PS. Biological factors do not account for the range of PS women experience, and little is known about the influence of psychosocial factors on PS. The aims of this study are to: estimate the prevalence of PS and associated disability in a population of women residing in King County, Washington; explore the clustering of symptoms in the perimenstruum; generate a typology of PS; and assess the relative contribution of women's socialization, current social context, ethnic group, gynecological history, health practices, and general health status to a model explaining the variance in PS, related disability and illness behavior. Nine hundred menstruating women between 18 and 45 years of age from 3 ethnic groups (Black, White and Asian) will be enrolled in the study through random sampling of households within selected census tracts. Women will be interviewed regarding their feminine socialization, current social context, gynecological history, health practices and general health status. They will be instructed in keeping a 90-day health diary in which they will record symptoms, disability and illness behaviors. During a telephone interview at the end of the study, they will be asked about the PS they typically experience, will rate their PS severity and treatability, and will describe coping methods they employ for PS. Pooled and stratum specific estimates of PS prevalence will be calculated. Dimensions of PS will be identified using factor analysis. Cluster analysis of cases will be used to generate a PS typology. Relative risk of experiencing PS types, given study factors, will be calculated. Multiple regression analysis will be used to test multivariate models of PS, PS disability, and illness behavior.